MMLongit: Function used to fit marginalized models

In binaryMM: Flexible Marginalized Models for Binary Correlated Outcomes

Function used to fit marginalized models

Description

Main function used to fit marginalized models. See mm() for a more user-friendly function and examples

Usage

MMLongit(
  params,
  id,
  X,
  Y,
  Xgam,
  Xsig,
  Q,
  weight = rep(1, length(Y)),
  offset = rep(0, length(Y)),
  stepmax = 1,
  steptol = 1e-06,
  hess.eps = 1e-07,
  AdaptiveQuad = FALSE,
  verbose = FALSE,
  iterlim
)

Arguments

params	a vector of initial values.
id	a vector of cluster identifiers.
X	a design matrix, including intercept, for the mean formula.
Y	a binary vector
Xgam	a design matrix for the transition formula.
Xsig	a design matrix for the latent variable formula.
Q	a scalar denoting the number of quadrature points.
weight	a vector of sampling weights.
offset	an optional offset term.
stepmax	a scalar
steptol	a scalar
hess.eps	a scalar
AdaptiveQuad	an indicator if adaptive quadrature is to be used. NOT CURRENTLY IMPLEMENTED.
verbose	an indicator if model output should be printed to the screen during maximization (or minimization of negative log-likelihood). See print.level in nlm.
iterlim	a scalar to denote the maximum iteration limit used by nlm. Default value is 100

Value

This function returns marginal parameters (beta) and dependence parameters (alpha) along with the associated covariance matrices.

binaryMM documentation built on Oct. 12, 2022, 1:06 a.m.